Area(s) of responsibility
Key Responsibilities
- Design and implement GenAI and Agentic AI solutions using Databricks Genie, Databricks Agent Bricks, Mosaic AI (model training, evaluation, prompt engineering, RAG)
- Experience Build LLM-powered use cases
- Design and build scalable data pipelines using Databricks, PySpark, and SQL
- Implement Delta Lake, Unity Catalog, and medallion architecture
- Optimize Spark jobs for performance, cost, and scalability
- Perform data ingestion, transformation, and enrichment from multiple sources
- Ensure data quality, reliability, and observability across pipelines
- Design and develop enterprise ontologies, taxonomies, vocabularies, and semantic data models.
- Support AI/ML workloads by preparing high‑quality, feature‑ready datasets
- Develop and fine-tune LLMs/ML models using Databricks MLflow and Mosaic AI
- Implement prompt engineering, model evaluation, and guardrails for enterprise GenAI use cases
- Integrate AI solutions with enterprise data and business workflows
